English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We find that images contain intrinsic structure that enables the reversal ofmany adversarial attacks. Attack vectors cause not only image classifiers tofail, but also collaterally disrupt incidental structure in the image. Wedemonstrate that modifying the attacked image to restore the natural structurewill reverse many types of attacks, providing a defense. Experimentsdemonstrate significantly improved robustness for several state-of-the-artmodels across the CIFAR-10, CIFAR-100, SVHN, and ImageNet datasets. Our resultsshow that our defense is still effective even if the attacker is aware of thedefense mechanism. Since our defense is deployed during inference instead oftraining, it is compatible with pre-trained networks as well as most otherdefenses. Our results suggest deep networks are vulnerable to adversarialexamples partly because their representations do not enforce the naturalstructure of images.

Adversarial Attacks are Reversible with Natural Supervision